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Copy path08.1.slade_aurum_paper_plots.R
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08.1.slade_aurum_paper_plots.R
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####################
## Description:
## - In this file we create the plots used in the paper + extended figures
####################
## Load libraries
library(tidyverse)
library(patchwork)
library(scales)
library(forestplot)
## Load functions required
source("11.01.slade_aurum_functions.R")
source("11.02.slade_aurum_set_data.R")
## make directory for outputs
dir.create("Plots/Paper")
## make directory for outputs
dir.create("Plots/Paper/Manuscript")
#### Main manuscript plots
#:------------------------------------------------------------------------------
# Figure 1: 3 panel plot:
# -A. Histogram of treatment effects - development cohort
# -B. Calibration plot for development cohort
# -C. Calibration plot for validation cohort
### A
bcf_model <- readRDS("Samples/SGLT2-GLP1/Aurum/response_model_bcf/bcf_model.rds")
data_dev <- cbind(mean = colMeans(bcf_model$tau)) %>%
as.data.frame()
plot_effect_dev <- hist_plot(data_dev, paste0("Development cohort (n=", format(nrow(data_dev),big.mark=",",scientific=FALSE), ")"), -15, 20) +
scale_y_continuous(label=comma) +
xlab("Predicted conditional average treatment effect (mmol/mol)")
### B
# load development cohort model calibration
ATE_adjust_validation_dev <- readRDS("Samples/SGLT2-GLP1/Aurum/response_model_bcf/assessment/ATE_adjust_validation_dev.rds")
# plot development cohort calibration
plot_ATE_adjust_validation_dev <- ATE_plot(ATE_adjust_validation_dev[["effects"]], "hba1c_diff.pred", "obs", "lci", "uci", -12, 12) +
theme(panel.grid.major = element_blank(), panel.grid.minor = element_blank()) +
ggtitle(paste0("Development cohort (n=", format(sum(ATE_adjust_validation_dev[["effects"]]$N),big.mark=",",scientific=FALSE), ")"))
### C
# load validation cohort model calibration
ATE_adjust_validation_val <- readRDS("Samples/SGLT2-GLP1/Aurum/response_model_bcf/assessment/ATE_adjust_validation_val.rds")
# plot validation cohort calibration
plot_ATE_adjust_validation_val <- ATE_plot(ATE_adjust_validation_val[["effects"]], "hba1c_diff.pred", "obs", "lci", "uci", -12, 12) +
theme(panel.grid.major = element_blank(), panel.grid.minor = element_blank()) +
ggtitle(paste0("Validation cohort (n=", format(sum(ATE_adjust_validation_val[["effects"]]$N),big.mark=",",scientific=FALSE), ")"))
plot_main_1.1 <- plot_effect_dev | plot_ATE_adjust_validation_dev | plot_ATE_adjust_validation_val
plot_main_1 <- plot_main_1.1 +
plot_annotation(tag_levels = "A",
theme = theme(legend.position = "bottom"))
pdf(width = 15, height = 6, "Plots/Paper/Manuscript/11.08.plot_main_1.pdf")
plot_main_1
dev.off()
#:------------------------------------------------------------------------------
# Figure 2:
#:--------------------------------------------------------------------------------
### Variables ranges across HbA1c benefit subgroups
interval_breaks <- c(-5, -3, 0, 3, 5)
full.cohort <- set_up_data_sglt2_glp1(dataset.type = "hba1c.train") %>%
# drop the variables with the most missingness (>40%)
select(-preacr, -preast, -prehaematocrit, -prehaemoglobin, -pretriglyceride) %>%
# only complete cases
drop_na() %>%
as.data.frame() %>%
select(patid, pated, posthba1cfinal, drugclass, unique(c(readRDS("Samples/SGLT2-GLP1/Aurum/response_model_bcf/variables_mu.rds"), readRDS("Samples/SGLT2-GLP1/Aurum/response_model_bcf/variables_tau.rds")))) %>%
rbind(
set_up_data_sglt2_glp1(dataset.type = "hba1c.test") %>%
# selected variables from SparseBCF
select(patid, pated, posthba1cfinal, drugclass, unique(c(readRDS("Samples/SGLT2-GLP1/Aurum/response_model_bcf/variables_mu.rds"), readRDS("Samples/SGLT2-GLP1/Aurum/response_model_bcf/variables_tau.rds")))) %>%
# only complete cases
drop_na() %>%
as.data.frame()
) %>%
left_join(readRDS("Samples/SGLT2-GLP1/Aurum/response_model_bcf/patient_effects.rds"), by = c("patid", "pated"))
group.full.cohort <- group_values(data = full.cohort,
variable = "effects",
breaks = interval_breaks) %>%
drop_na(intervals)
group.full.cohort <- group.full.cohort %>%
mutate(intervals = ifelse(intervals == levels(group.full.cohort$intervals)[1], "SGLT2i benefit >5 mmol/mol",
ifelse(intervals == levels(group.full.cohort$intervals)[2], "SGLT2i benefit 3-5 mmol/mol",
ifelse(intervals == levels(group.full.cohort$intervals)[3], "SGLT2i benefit 0-3 mmol/mol",
ifelse(intervals == levels(group.full.cohort$intervals)[4], "GLP1-RA benefit 0-3 mmol/mol",
ifelse(intervals == levels(group.full.cohort$intervals)[5], "GLP1-RA benefit 3-5 mmol/mol",
ifelse(intervals == levels(group.full.cohort$intervals)[6], "GLP1-RA benefit >5 mmol/mol", intervals))))))
) %>%
mutate(intervals = factor(intervals, levels = c("SGLT2i benefit >5 mmol/mol", "SGLT2i benefit 3-5 mmol/mol", "SGLT2i benefit 0-3 mmol/mol", "GLP1-RA benefit 0-3 mmol/mol", "GLP1-RA benefit 3-5 mmol/mol", "GLP1-RA benefit >5 mmol/mol")))
levels(group.full.cohort$sex) <- c("Females", "Males")
levels(group.full.cohort$ncurrtx) <- c("0", "1", "2", "3", "4+")
plot_t2dmduration_strata <- group.full.cohort %>%
select(intervals, t2dmduration) %>%
drop_na() %>%
ggplot(aes(x = intervals, y = t2dmduration)) +
geom_boxplot(outlier.shape = NA, fill = c(rep("#f1a340", 3), rep("dodgerblue2", 3)), alpha = c(1, 0.6, 0.2, 0.2, 0.6, 1)) +
ggtitle("Duration of diabetes") +
ylim(0, 30) +
theme_bw() +
theme(axis.title = element_blank(),
axis.text.x = element_text(angle = 70, vjust = 1, hjust = 1),
strip.background = element_rect(fill = "white"),
legend.title = element_blank(),
plot.title = element_text(hjust = 0.5))
# plot_ncurrtx_strata <- group.full.cohort %>%
# select(ncurrtx, intervals) %>%
# ggplot(aes(x = intervals)) +
# geom_bar(aes(fill = ncurrtx), position = "fill") +
# ggtitle("Number of other current\nglucose-lowering drugs") +
# scale_y_continuous(labels = scales::percent) +
# theme_bw() +
# theme(legend.position = "bottom",
# axis.title = element_blank(),
# axis.text.x = element_text(angle = 70, vjust = 1, hjust = 1),
# strip.background = element_rect(fill = "white"),
# legend.title = element_blank(),
# plot.title = element_text(hjust = 0.5))
plot_sex_strata <- group.full.cohort %>%
select(sex, intervals) %>%
ggplot(aes(x = intervals)) +
geom_bar(aes(fill = sex), position = "fill") +
ggtitle("Sex") +
ylab("Percentage (%)") +
scale_y_continuous(labels = scales::percent) +
scale_fill_brewer(palette = "Accent") +
theme_bw() +
annotate("point", x = 1, y = -0.08, shape = 15, colour = "#f1a340", size = 5, alpha = 1) +
annotate("point", x = 2, y = -0.08, shape = 15, colour = "#f1a340", size = 5, alpha = 0.6) +
annotate("point", x = 3, y = -0.08, shape = 15, colour = "#f1a340", size = 5, alpha = 0.2) +
annotate("point", x = 4, y = -0.08, shape = 15, colour = "dodgerblue2", size = 5, alpha = 0.2) +
annotate("point", x = 5, y = -0.08, shape = 15, colour = "dodgerblue2", size = 5, alpha = 0.6) +
annotate("point", x = 6, y = -0.08, shape = 15, colour = "dodgerblue2", size = 5, alpha = 1) +
coord_cartesian(ylim = c(0, 1), clip = "off") +
theme(legend.position = "bottom",
axis.text.y = element_text(size = 13),
axis.text.x = element_blank(),
axis.title.y = element_text(size = 13),
legend.text = element_text(size= 13 ),
legend.title = element_text(size = 13),
axis.title.x = element_text(vjust = -5, colour = "white"),
strip.background = element_rect(fill = "white"),
plot.title = element_text(hjust = 0.5)) +
guides(fill=guide_legend(title="Sex", title.position="top", title.hjust = 0.5))
plot_prehba1c_strata <- group.full.cohort %>%
select(intervals, prehba1c) %>%
drop_na() %>%
ggplot(aes(x = intervals, y = prehba1c)) +
geom_point(aes(fill = intervals, colour = intervals), alpha = 0, shape = 15, size = 5) +
geom_boxplot(outlier.shape = NA, aes(fill = intervals), alpha = c(1, 0.6, 0.2, 0.2, 0.6, 1), show.legend = F) +
ggtitle("Baseline HbA1c") +
ylab("Baseline HbA1c (mmol/mol)") +
theme_bw() +
annotate("point", x = 1, y = 42, shape = 15, colour = "#f1a340", size = 5, alpha = 1) +
annotate("point", x = 2, y = 42, shape = 15, colour = "#f1a340", size = 5, alpha = 0.6) +
annotate("point", x = 3, y = 42, shape = 15, colour = "#f1a340", size = 5, alpha = 0.2) +
annotate("point", x = 4, y = 42, shape = 15, colour = "dodgerblue2", size = 5, alpha = 0.2) +
annotate("point", x = 5, y = 42, shape = 15, colour = "dodgerblue2", size = 5, alpha = 0.6) +
annotate("point", x = 6, y = 42, shape = 15, colour = "dodgerblue2", size = 5, alpha = 1) +
coord_cartesian(ylim = c(50, 150), clip = "off") +
scale_y_continuous(breaks = c(53, 64, 75, 86, 97, 108, 119, 150)) +
theme(legend.position = "bottom",
axis.text.y = element_text(size = 13),
axis.text.x = element_blank(),
axis.title.y = element_text(size = 13),
legend.text = element_text(size= 13 ),
legend.title = element_text(size = 13),
axis.title.x = element_text(vjust = -5, colour = "white"),
strip.background = element_rect(fill = "white"),
plot.title = element_text(hjust = 0.5),
panel.grid.minor = element_blank()) +
scale_fill_manual(
name = paste0("HbA1c benefit (mmol/mol) [n=", format(nrow(group.full.cohort),big.mark=",",scientific=FALSE),"]"),
labels = c(paste0("SGLT2i > 5 [n=", format(group.full.cohort %>% filter(intervals == levels(group.full.cohort$intervals)[1]) %>% nrow(),big.mark=",",scientific=FALSE), "]"),
paste0("SGLT2i 3 - 5 [n=", format(group.full.cohort %>% filter(intervals == levels(group.full.cohort$intervals)[2]) %>% nrow(),big.mark=",",scientific=FALSE), "]"),
paste0("SGLT2i 0 - 3 [n=", format(group.full.cohort %>% filter(intervals == levels(group.full.cohort$intervals)[3]) %>% nrow(),big.mark=",",scientific=FALSE), "]"),
paste0("GLP1-RA > 5 [n=", format(group.full.cohort %>% filter(intervals == levels(group.full.cohort$intervals)[4]) %>% nrow(),big.mark=",",scientific=FALSE), "]"),
paste0("GLP1-RA 3 - 5 [n=", format(group.full.cohort %>% filter(intervals == levels(group.full.cohort$intervals)[5]) %>% nrow(),big.mark=",",scientific=FALSE), "]"),
paste0("GLP1-RA 0 - 3 [n=", format(group.full.cohort %>% filter(intervals == levels(group.full.cohort$intervals)[6]) %>% nrow(),big.mark=",",scientific=FALSE), "]")),
breaks = c(levels(group.full.cohort$intervals)[1], levels(group.full.cohort$intervals)[2], levels(group.full.cohort$intervals)[3], levels(group.full.cohort$intervals)[6], levels(group.full.cohort$intervals)[5], levels(group.full.cohort$intervals)[4]),
values = c("SGLT2i benefit >5 mmol/mol" = "#f1a340",
"SGLT2i benefit 3-5 mmol/mol" = "#f1a340",
"SGLT2i benefit 0-3 mmol/mol" = "#f1a340",
"GLP1-RA benefit 0-3 mmol/mol" = "dodgerblue2",
"GLP1-RA benefit 3-5 mmol/mol" = "dodgerblue2",
"GLP1-RA benefit >5 mmol/mol" = "dodgerblue2")
) +
scale_colour_manual(
name = paste0("HbA1c benefit (mmol/mol) [n=", format(nrow(group.full.cohort),big.mark=",",scientific=FALSE),"]"),
labels = c(paste0("SGLT2i > 5 [n=", format(group.full.cohort %>% filter(intervals == levels(group.full.cohort$intervals)[1]) %>% nrow(),big.mark=",",scientific=FALSE), "]"),
paste0("SGLT2i 3 - 5 [n=", format(group.full.cohort %>% filter(intervals == levels(group.full.cohort$intervals)[2]) %>% nrow(),big.mark=",",scientific=FALSE), "]"),
paste0("SGLT2i 0 - 3 [n=", format(group.full.cohort %>% filter(intervals == levels(group.full.cohort$intervals)[3]) %>% nrow(),big.mark=",",scientific=FALSE), "]"),
paste0("GLP1-RA > 5 [n=", format(group.full.cohort %>% filter(intervals == levels(group.full.cohort$intervals)[4]) %>% nrow(),big.mark=",",scientific=FALSE), "]"),
paste0("GLP1-RA 3 - 5 [n=", format(group.full.cohort %>% filter(intervals == levels(group.full.cohort$intervals)[5]) %>% nrow(),big.mark=",",scientific=FALSE), "]"),
paste0("GLP1-RA 0 - 3 [n=", format(group.full.cohort %>% filter(intervals == levels(group.full.cohort$intervals)[6]) %>% nrow(),big.mark=",",scientific=FALSE), "]")),
breaks = c(levels(group.full.cohort$intervals)[1], levels(group.full.cohort$intervals)[2], levels(group.full.cohort$intervals)[3], levels(group.full.cohort$intervals)[6], levels(group.full.cohort$intervals)[5], levels(group.full.cohort$intervals)[4]),
values = c("SGLT2i benefit >5 mmol/mol" = "#f1a340",
"SGLT2i benefit 3-5 mmol/mol" = "#f1a340",
"SGLT2i benefit 0-3 mmol/mol" = "#f1a340",
"GLP1-RA benefit 0-3 mmol/mol" = "dodgerblue2",
"GLP1-RA benefit 3-5 mmol/mol" = "dodgerblue2",
"GLP1-RA benefit >5 mmol/mol" = "dodgerblue2")
) +
guides(
fill = guide_legend(title.position="top", title.hjust = 0.5, override.aes = list(alpha = c(1, 0.6, 0.2, 1, 0.6, 0.2)), shape = c(15,15,15,15,15,15), ncol = 2, nrow = 3),
colour = guide_legend(title.position="top", title.hjust = 0.5, override.aes = list(alpha = c(1, 0.6, 0.2, 1, 0.6, 0.2)), shape = c(15,15,15,15,15,15), ncol = 2, nrow = 3)
)
plot_preegfr_strata <- group.full.cohort %>%
select(intervals, preegfr) %>%
drop_na() %>%
ggplot(aes(x = intervals, y = preegfr)) +
geom_point(aes(fill = intervals, colour = intervals), alpha = 0, shape = 15, size = 5) +
geom_boxplot(outlier.shape = NA, aes(fill = intervals), alpha = c(1, 0.6, 0.2, 0.2, 0.6, 1), show.legend = F) +
ggtitle("eGFR") +
ylab(expression(paste("eGFR (mL/min/1.3", m^{2}, ")"))) +
scale_y_continuous(breaks = c(30, 60, 90, 120, 150)) +
theme_bw() +
annotate("point", x = 1, y = 19.5, shape = 15, colour = "#f1a340", size = 5, alpha = 1) +
annotate("point", x = 2, y = 19.5, shape = 15, colour = "#f1a340", size = 5, alpha = 0.6) +
annotate("point", x = 3, y = 19.5, shape = 15, colour = "#f1a340", size = 5, alpha = 0.2) +
annotate("point", x = 4, y = 19.5, shape = 15, colour = "dodgerblue2", size = 5, alpha = 0.2) +
annotate("point", x = 5, y = 19.5, shape = 15, colour = "dodgerblue2", size = 5, alpha = 0.6) +
annotate("point", x = 6, y = 19.5, shape = 15, colour = "dodgerblue2", size = 5, alpha = 1) +
coord_cartesian(ylim = c(30, 150), clip = "off") +
theme(legend.position = "bottom",
axis.text.y = element_text(size = 13),
axis.text.x = element_blank(),
axis.title.y = element_text(size = 13),
legend.text = element_text(size= 13 ),
legend.title = element_text(size = 13),
axis.title.x = element_text(vjust = -5, colour = "white"),
strip.background = element_rect(fill = "white"),
plot.title = element_text(hjust = 0.5)) +
scale_fill_manual(
name = paste0("HbA1c benefit (mmol/mol) [n=", format(nrow(group.full.cohort),big.mark=",",scientific=FALSE),"]"),
labels = c(paste0("SGLT2i > 5 [n=", format(group.full.cohort %>% filter(intervals == levels(group.full.cohort$intervals)[1]) %>% nrow(),big.mark=",",scientific=FALSE), "]"),
paste0("SGLT2i 3 - 5 [n=", format(group.full.cohort %>% filter(intervals == levels(group.full.cohort$intervals)[2]) %>% nrow(),big.mark=",",scientific=FALSE), "]"),
paste0("SGLT2i 0 - 3 [n=", format(group.full.cohort %>% filter(intervals == levels(group.full.cohort$intervals)[3]) %>% nrow(),big.mark=",",scientific=FALSE), "]"),
paste0("GLP1-RA > 5 [n=", format(group.full.cohort %>% filter(intervals == levels(group.full.cohort$intervals)[4]) %>% nrow(),big.mark=",",scientific=FALSE), "]"),
paste0("GLP1-RA 3 - 5 [n=", format(group.full.cohort %>% filter(intervals == levels(group.full.cohort$intervals)[5]) %>% nrow(),big.mark=",",scientific=FALSE), "]"),
paste0("GLP1-RA 0 - 3 [n=", format(group.full.cohort %>% filter(intervals == levels(group.full.cohort$intervals)[6]) %>% nrow(),big.mark=",",scientific=FALSE), "]")),
breaks = c(levels(group.full.cohort$intervals)[1], levels(group.full.cohort$intervals)[2], levels(group.full.cohort$intervals)[3], levels(group.full.cohort$intervals)[6], levels(group.full.cohort$intervals)[5], levels(group.full.cohort$intervals)[4]),
values = c("SGLT2i benefit >5 mmol/mol" = "#f1a340",
"SGLT2i benefit 3-5 mmol/mol" = "#f1a340",
"SGLT2i benefit 0-3 mmol/mol" = "#f1a340",
"GLP1-RA benefit 0-3 mmol/mol" = "dodgerblue2",
"GLP1-RA benefit 3-5 mmol/mol" = "dodgerblue2",
"GLP1-RA benefit >5 mmol/mol" = "dodgerblue2")
) +
scale_colour_manual(
name = paste0("HbA1c benefit (mmol/mol) [n=", format(nrow(group.full.cohort),big.mark=",",scientific=FALSE),"]"),
labels = c(paste0("SGLT2i > 5 [n=", format(group.full.cohort %>% filter(intervals == levels(group.full.cohort$intervals)[1]) %>% nrow(),big.mark=",",scientific=FALSE), "]"),
paste0("SGLT2i 3 - 5 [n=", format(group.full.cohort %>% filter(intervals == levels(group.full.cohort$intervals)[2]) %>% nrow(),big.mark=",",scientific=FALSE), "]"),
paste0("SGLT2i 0 - 3 [n=", format(group.full.cohort %>% filter(intervals == levels(group.full.cohort$intervals)[3]) %>% nrow(),big.mark=",",scientific=FALSE), "]"),
paste0("GLP1-RA > 5 [n=", format(group.full.cohort %>% filter(intervals == levels(group.full.cohort$intervals)[4]) %>% nrow(),big.mark=",",scientific=FALSE), "]"),
paste0("GLP1-RA 3 - 5 [n=", format(group.full.cohort %>% filter(intervals == levels(group.full.cohort$intervals)[5]) %>% nrow(),big.mark=",",scientific=FALSE), "]"),
paste0("GLP1-RA 0 - 3 [n=", format(group.full.cohort %>% filter(intervals == levels(group.full.cohort$intervals)[6]) %>% nrow(),big.mark=",",scientific=FALSE), "]")),
breaks = c(levels(group.full.cohort$intervals)[1], levels(group.full.cohort$intervals)[2], levels(group.full.cohort$intervals)[3], levels(group.full.cohort$intervals)[6], levels(group.full.cohort$intervals)[5], levels(group.full.cohort$intervals)[4]),
values = c("SGLT2i benefit >5 mmol/mol" = "#f1a340",
"SGLT2i benefit 3-5 mmol/mol" = "#f1a340",
"SGLT2i benefit 0-3 mmol/mol" = "#f1a340",
"GLP1-RA benefit 0-3 mmol/mol" = "dodgerblue2",
"GLP1-RA benefit 3-5 mmol/mol" = "dodgerblue2",
"GLP1-RA benefit >5 mmol/mol" = "dodgerblue2")
) +
guides(
fill = guide_legend(title.position="top", title.hjust = 0.5, override.aes = list(alpha = c(1, 0.6, 0.2, 1, 0.6, 0.2)), shape = c(15,15,15,15,15,15), ncol = 2, nrow = 3),
colour = guide_legend(title.position="top", title.hjust = 0.5, override.aes = list(alpha = c(1, 0.6, 0.2, 1, 0.6, 0.2)), shape = c(15,15,15,15,15,15), ncol = 2, nrow = 3)
)
plot_agetx_strata <- group.full.cohort %>%
select(intervals, agetx) %>%
drop_na() %>%
ggplot(aes(x = intervals, y = agetx)) +
geom_point(aes(fill = intervals, colour = intervals), alpha = 0, shape = 15, size = 5) +
geom_boxplot(outlier.shape = NA, aes(fill = intervals), alpha = c(1, 0.6, 0.2, 0.2, 0.6, 1), show.legend = F) +
ggtitle("Current age") +
ylab("Current age (years)") +
theme_bw() +
annotate("point", x = 1, y = 11, shape = 15, colour = "#f1a340", size = 5, alpha = 1) +
annotate("point", x = 2, y = 11, shape = 15, colour = "#f1a340", size = 5, alpha = 0.6) +
annotate("point", x = 3, y = 11, shape = 15, colour = "#f1a340", size = 5, alpha = 0.2) +
annotate("point", x = 4, y = 11, shape = 15, colour = "dodgerblue2", size = 5, alpha = 0.2) +
annotate("point", x = 5, y = 11, shape = 15, colour = "dodgerblue2", size = 5, alpha = 0.6) +
annotate("point", x = 6, y = 11, shape = 15, colour = "dodgerblue2", size = 5, alpha = 1) +
coord_cartesian(ylim = c(18, 100), clip = "off") +
theme(legend.position = "bottom",
axis.text.y = element_text(size = 13),
axis.text.x = element_blank(),
axis.title.y = element_text(size = 13),
legend.text = element_text(size= 13 ),
legend.title = element_text(size = 13),
axis.title.x = element_text(vjust = -5, colour = "white"),
strip.background = element_rect(fill = "white"),
plot.title = element_text(hjust = 0.5)) +
scale_fill_manual(
name = paste0("HbA1c benefit (mmol/mol) [n=", format(nrow(group.full.cohort),big.mark=",",scientific=FALSE),"]"),
labels = c(paste0("SGLT2i > 5 [n=", format(group.full.cohort %>% filter(intervals == levels(group.full.cohort$intervals)[1]) %>% nrow(),big.mark=",",scientific=FALSE), "]"),
paste0("SGLT2i 3 - 5 [n=", format(group.full.cohort %>% filter(intervals == levels(group.full.cohort$intervals)[2]) %>% nrow(),big.mark=",",scientific=FALSE), "]"),
paste0("SGLT2i 0 - 3 [n=", format(group.full.cohort %>% filter(intervals == levels(group.full.cohort$intervals)[3]) %>% nrow(),big.mark=",",scientific=FALSE), "]"),
paste0("GLP1-RA > 5 [n=", format(group.full.cohort %>% filter(intervals == levels(group.full.cohort$intervals)[4]) %>% nrow(),big.mark=",",scientific=FALSE), "]"),
paste0("GLP1-RA 3 - 5 [n=", format(group.full.cohort %>% filter(intervals == levels(group.full.cohort$intervals)[5]) %>% nrow(),big.mark=",",scientific=FALSE), "]"),
paste0("GLP1-RA 0 - 3 [n=", format(group.full.cohort %>% filter(intervals == levels(group.full.cohort$intervals)[6]) %>% nrow(),big.mark=",",scientific=FALSE), "]")),
breaks = c(levels(group.full.cohort$intervals)[1], levels(group.full.cohort$intervals)[2], levels(group.full.cohort$intervals)[3], levels(group.full.cohort$intervals)[6], levels(group.full.cohort$intervals)[5], levels(group.full.cohort$intervals)[4]),
values = c("SGLT2i benefit >5 mmol/mol" = "#f1a340",
"SGLT2i benefit 3-5 mmol/mol" = "#f1a340",
"SGLT2i benefit 0-3 mmol/mol" = "#f1a340",
"GLP1-RA benefit 0-3 mmol/mol" = "dodgerblue2",
"GLP1-RA benefit 3-5 mmol/mol" = "dodgerblue2",
"GLP1-RA benefit >5 mmol/mol" = "dodgerblue2")
) +
scale_colour_manual(
name = paste0("HbA1c benefit (mmol/mol) [n=", format(nrow(group.full.cohort),big.mark=",",scientific=FALSE),"]"),
labels = c(paste0("SGLT2i > 5 [n=", format(group.full.cohort %>% filter(intervals == levels(group.full.cohort$intervals)[1]) %>% nrow(),big.mark=",",scientific=FALSE), "]"),
paste0("SGLT2i 3 - 5 [n=", format(group.full.cohort %>% filter(intervals == levels(group.full.cohort$intervals)[2]) %>% nrow(),big.mark=",",scientific=FALSE), "]"),
paste0("SGLT2i 0 - 3 [n=", format(group.full.cohort %>% filter(intervals == levels(group.full.cohort$intervals)[3]) %>% nrow(),big.mark=",",scientific=FALSE), "]"),
paste0("GLP1-RA > 5 [n=", format(group.full.cohort %>% filter(intervals == levels(group.full.cohort$intervals)[4]) %>% nrow(),big.mark=",",scientific=FALSE), "]"),
paste0("GLP1-RA 3 - 5 [n=", format(group.full.cohort %>% filter(intervals == levels(group.full.cohort$intervals)[5]) %>% nrow(),big.mark=",",scientific=FALSE), "]"),
paste0("GLP1-RA 0 - 3 [n=", format(group.full.cohort %>% filter(intervals == levels(group.full.cohort$intervals)[6]) %>% nrow(),big.mark=",",scientific=FALSE), "]")),
breaks = c(levels(group.full.cohort$intervals)[1], levels(group.full.cohort$intervals)[2], levels(group.full.cohort$intervals)[3], levels(group.full.cohort$intervals)[6], levels(group.full.cohort$intervals)[5], levels(group.full.cohort$intervals)[4]),
values = c("SGLT2i benefit >5 mmol/mol" = "#f1a340",
"SGLT2i benefit 3-5 mmol/mol" = "#f1a340",
"SGLT2i benefit 0-3 mmol/mol" = "#f1a340",
"GLP1-RA benefit 0-3 mmol/mol" = "dodgerblue2",
"GLP1-RA benefit 3-5 mmol/mol" = "dodgerblue2",
"GLP1-RA benefit >5 mmol/mol" = "dodgerblue2")
) +
guides(
fill = guide_legend(title.position="top", title.hjust = 0.5, override.aes = list(alpha = c(1, 0.6, 0.2, 1, 0.6, 0.2)), shape = c(15,15,15,15,15,15), ncol = 2, nrow = 3),
colour = guide_legend(title.position="top", title.hjust = 0.5, override.aes = list(alpha = c(1, 0.6, 0.2, 1, 0.6, 0.2)), shape = c(15,15,15,15,15,15), ncol = 2, nrow = 3)
)
plot_prebmi_strata <- group.full.cohort %>%
select(intervals, prebmi) %>%
drop_na() %>%
ggplot(aes(x = intervals, y = prebmi)) +
geom_point(aes(fill = intervals, colour = intervals), alpha = 0, shape = 15, size = 5) +
geom_boxplot(outlier.shape = NA, aes(fill = intervals), alpha = c(1, 0.6, 0.2, 0.2, 0.6, 1), show.legend = F) +
ggtitle("BMI") +
ylab(expression(paste("BMI (kg/", m^{2}, ")"))) +
theme_bw() +
annotate("point", x = 1, y = 11.5, shape = 15, colour = "#f1a340", size = 5, alpha = 1) +
annotate("point", x = 2, y = 11.5, shape = 15, colour = "#f1a340", size = 5, alpha = 0.6) +
annotate("point", x = 3, y = 11.5, shape = 15, colour = "#f1a340", size = 5, alpha = 0.2) +
annotate("point", x = 4, y = 11.5, shape = 15, colour = "dodgerblue2", size = 5, alpha = 0.2) +
annotate("point", x = 5, y = 11.5, shape = 15, colour = "dodgerblue2", size = 5, alpha = 0.6) +
annotate("point", x = 6, y = 11.5, shape = 15, colour = "dodgerblue2", size = 5, alpha = 1) +
coord_cartesian(ylim = c(15, 55), clip = "off") +
theme(legend.position = "bottom",
axis.text.y = element_text(size = 13),
axis.text.x = element_blank(),
axis.title.y = element_text(size = 13),
legend.text = element_text(size= 13 ),
legend.title = element_text(size = 13),
axis.title.x = element_text(vjust = -5, colour = "white"),
strip.background = element_rect(fill = "white"),
plot.title = element_text(hjust = 0.5)) +
scale_fill_manual(
name = paste0("HbA1c benefit (mmol/mol) [n=", format(nrow(group.full.cohort),big.mark=",",scientific=FALSE),"]"),
labels = c(paste0("SGLT2i > 5 [n=", format(group.full.cohort %>% filter(intervals == levels(group.full.cohort$intervals)[1]) %>% nrow(),big.mark=",",scientific=FALSE), "]"),
paste0("SGLT2i 3 - 5 [n=", format(group.full.cohort %>% filter(intervals == levels(group.full.cohort$intervals)[2]) %>% nrow(),big.mark=",",scientific=FALSE), "]"),
paste0("SGLT2i 0 - 3 [n=", format(group.full.cohort %>% filter(intervals == levels(group.full.cohort$intervals)[3]) %>% nrow(),big.mark=",",scientific=FALSE), "]"),
paste0("GLP1-RA > 5 [n=", format(group.full.cohort %>% filter(intervals == levels(group.full.cohort$intervals)[4]) %>% nrow(),big.mark=",",scientific=FALSE), "]"),
paste0("GLP1-RA 3 - 5 [n=", format(group.full.cohort %>% filter(intervals == levels(group.full.cohort$intervals)[5]) %>% nrow(),big.mark=",",scientific=FALSE), "]"),
paste0("GLP1-RA 0 - 3 [n=", format(group.full.cohort %>% filter(intervals == levels(group.full.cohort$intervals)[6]) %>% nrow(),big.mark=",",scientific=FALSE), "]")),
breaks = c(levels(group.full.cohort$intervals)[1], levels(group.full.cohort$intervals)[2], levels(group.full.cohort$intervals)[3], levels(group.full.cohort$intervals)[6], levels(group.full.cohort$intervals)[5], levels(group.full.cohort$intervals)[4]),
values = c("SGLT2i benefit >5 mmol/mol" = "#f1a340",
"SGLT2i benefit 3-5 mmol/mol" = "#f1a340",
"SGLT2i benefit 0-3 mmol/mol" = "#f1a340",
"GLP1-RA benefit 0-3 mmol/mol" = "dodgerblue2",
"GLP1-RA benefit 3-5 mmol/mol" = "dodgerblue2",
"GLP1-RA benefit >5 mmol/mol" = "dodgerblue2")
) +
scale_colour_manual(
name = paste0("HbA1c benefit (mmol/mol) [n=", format(nrow(group.full.cohort),big.mark=",",scientific=FALSE),"]"),
labels = c(paste0("SGLT2i > 5 [n=", format(group.full.cohort %>% filter(intervals == levels(group.full.cohort$intervals)[1]) %>% nrow(),big.mark=",",scientific=FALSE), "]"),
paste0("SGLT2i 3 - 5 [n=", format(group.full.cohort %>% filter(intervals == levels(group.full.cohort$intervals)[2]) %>% nrow(),big.mark=",",scientific=FALSE), "]"),
paste0("SGLT2i 0 - 3 [n=", format(group.full.cohort %>% filter(intervals == levels(group.full.cohort$intervals)[3]) %>% nrow(),big.mark=",",scientific=FALSE), "]"),
paste0("GLP1-RA > 5 [n=", format(group.full.cohort %>% filter(intervals == levels(group.full.cohort$intervals)[4]) %>% nrow(),big.mark=",",scientific=FALSE), "]"),
paste0("GLP1-RA 3 - 5 [n=", format(group.full.cohort %>% filter(intervals == levels(group.full.cohort$intervals)[5]) %>% nrow(),big.mark=",",scientific=FALSE), "]"),
paste0("GLP1-RA 0 - 3 [n=", format(group.full.cohort %>% filter(intervals == levels(group.full.cohort$intervals)[6]) %>% nrow(),big.mark=",",scientific=FALSE), "]")),
breaks = c(levels(group.full.cohort$intervals)[1], levels(group.full.cohort$intervals)[2], levels(group.full.cohort$intervals)[3], levels(group.full.cohort$intervals)[6], levels(group.full.cohort$intervals)[5], levels(group.full.cohort$intervals)[4]),
values = c("SGLT2i benefit >5 mmol/mol" = "#f1a340",
"SGLT2i benefit 3-5 mmol/mol" = "#f1a340",
"SGLT2i benefit 0-3 mmol/mol" = "#f1a340",
"GLP1-RA benefit 0-3 mmol/mol" = "dodgerblue2",
"GLP1-RA benefit 3-5 mmol/mol" = "dodgerblue2",
"GLP1-RA benefit >5 mmol/mol" = "dodgerblue2")
) +
guides(
fill = guide_legend(title.position="top", title.hjust = 0.5, override.aes = list(alpha = c(1, 0.6, 0.2, 1, 0.6, 0.2)), shape = c(15,15,15,15,15,15), ncol = 2, nrow = 3),
colour = guide_legend(title.position="top", title.hjust = 0.5, override.aes = list(alpha = c(1, 0.6, 0.2, 1, 0.6, 0.2)), shape = c(15,15,15,15,15,15), ncol = 2, nrow = 3)
)
plot_main_2 <- patchwork::wrap_plots(list(
plot_sex_strata +
theme(
legend.position = "bottom"
),
patchwork::wrap_plots(list(
plot_prehba1c_strata,
plot_preegfr_strata,
plot_agetx_strata,
plot_prebmi_strata
), nrow = 1) +
plot_layout(guides = "collect") &
theme(
legend.position = "bottom"
)
), nrow = 1) +
plot_layout(
widths = c(1, 5)
)
pdf(width = 17, height = 8, "Plots/Paper/Manuscript/11.08.plot_main_2.pdf")
plot_main_2
dev.off()
# pdf(width = 5, height = 7, "Plots/Paper/Sup_Mat/11.08.plot_sup_15.pdf")
# plot_t2dmduration_strata
# dev.off()
#####################
plot_sex_strata <- group.full.cohort %>%
select(sex, intervals) %>%
ggplot(aes(x = intervals)) +
geom_bar(aes(fill = sex), position = "fill") +
ggtitle("Sex") +
ylab("Percentage (%)") +
scale_y_continuous(labels = scales::percent) +
scale_fill_brewer(palette = "Accent") +
theme_bw() +
annotate("point", x = 1, y = -0.08, shape = 15, colour = "#f1a340", size = 5, alpha = 1) +
annotate("point", x = 2, y = -0.08, shape = 15, colour = "#f1a340", size = 5, alpha = 0.6) +
annotate("point", x = 3, y = -0.08, shape = 15, colour = "#f1a340", size = 5, alpha = 0.2) +
annotate("point", x = 4, y = -0.08, shape = 15, colour = "dodgerblue2", size = 5, alpha = 0.2) +
annotate("point", x = 5, y = -0.08, shape = 15, colour = "dodgerblue2", size = 5, alpha = 0.6) +
annotate("point", x = 6, y = -0.08, shape = 15, colour = "dodgerblue2", size = 5, alpha = 1) +
coord_cartesian(ylim = c(0, 1), clip = "off") +
theme(legend.position = "bottom",
axis.text.y = element_text(size = 13),
axis.text.x = element_blank(),
axis.title.y = element_text(size = 13),
legend.text = element_text(size= 13 ),
legend.title = element_text(size = 13),
axis.title.x = element_text(vjust = -5, colour = "white"),
strip.background = element_rect(fill = "white"),
plot.title = element_text(hjust = 0.5)) +
guides(fill=guide_legend(title="Sex", title.position="top", title.hjust = 0.5))
plot_prehba1c_strata <- group.full.cohort %>%
select(intervals, prehba1c) %>%
drop_na() %>%
ggplot(aes(x = intervals, y = prehba1c)) +
geom_point(aes(fill = intervals, colour = intervals), alpha = 0, shape = 15, size = 5) +
geom_boxplot(aes(fill = intervals), alpha = c(1, 0.6, 0.2, 0.2, 0.6, 1), show.legend = F) +
ggtitle("Baseline HbA1c") +
ylab("Baseline HbA1c (mmol/mol)") +
theme_bw() +
annotate("point", x = 1, y = 40, shape = 15, colour = "#f1a340", size = 5, alpha = 1) +
annotate("point", x = 2, y = 40, shape = 15, colour = "#f1a340", size = 5, alpha = 0.6) +
annotate("point", x = 3, y = 40, shape = 15, colour = "#f1a340", size = 5, alpha = 0.2) +
annotate("point", x = 4, y = 40, shape = 15, colour = "dodgerblue2", size = 5, alpha = 0.2) +
annotate("point", x = 5, y = 40, shape = 15, colour = "dodgerblue2", size = 5, alpha = 0.6) +
annotate("point", x = 6, y = 40, shape = 15, colour = "dodgerblue2", size = 5, alpha = 1) +
coord_cartesian(ylim = c(50, 180), clip = "off") +
scale_y_continuous(breaks = c(53, 64, 75, 86, 97, 108, 119, 150)) +
theme(legend.position = "bottom",
axis.text.y = element_text(size = 13),
axis.text.x = element_blank(),
axis.title.y = element_text(size = 13),
legend.text = element_text(size= 13 ),
legend.title = element_text(size = 13),
axis.title.x = element_text(vjust = -5, colour = "white"),
strip.background = element_rect(fill = "white"),
plot.title = element_text(hjust = 0.5),
panel.grid.minor = element_blank()) +
scale_fill_manual(
name = paste0("HbA1c benefit (mmol/mol) [n=", format(nrow(group.full.cohort),big.mark=",",scientific=FALSE),"]"),
labels = c(paste0("SGLT2i > 5 [n=", format(group.full.cohort %>% filter(intervals == levels(group.full.cohort$intervals)[1]) %>% nrow(),big.mark=",",scientific=FALSE), "]"),
paste0("SGLT2i 3 - 5 [n=", format(group.full.cohort %>% filter(intervals == levels(group.full.cohort$intervals)[2]) %>% nrow(),big.mark=",",scientific=FALSE), "]"),
paste0("SGLT2i 0 - 3 [n=", format(group.full.cohort %>% filter(intervals == levels(group.full.cohort$intervals)[3]) %>% nrow(),big.mark=",",scientific=FALSE), "]"),
paste0("GLP1-RA > 5 [n=", format(group.full.cohort %>% filter(intervals == levels(group.full.cohort$intervals)[4]) %>% nrow(),big.mark=",",scientific=FALSE), "]"),
paste0("GLP1-RA 3 - 5 [n=", format(group.full.cohort %>% filter(intervals == levels(group.full.cohort$intervals)[5]) %>% nrow(),big.mark=",",scientific=FALSE), "]"),
paste0("GLP1-RA 0 - 3 [n=", format(group.full.cohort %>% filter(intervals == levels(group.full.cohort$intervals)[6]) %>% nrow(),big.mark=",",scientific=FALSE), "]")),
breaks = c(levels(group.full.cohort$intervals)[1], levels(group.full.cohort$intervals)[2], levels(group.full.cohort$intervals)[3], levels(group.full.cohort$intervals)[6], levels(group.full.cohort$intervals)[5], levels(group.full.cohort$intervals)[4]),
values = c("SGLT2i benefit >5 mmol/mol" = "#f1a340",
"SGLT2i benefit 3-5 mmol/mol" = "#f1a340",
"SGLT2i benefit 0-3 mmol/mol" = "#f1a340",
"GLP1-RA benefit 0-3 mmol/mol" = "dodgerblue2",
"GLP1-RA benefit 3-5 mmol/mol" = "dodgerblue2",
"GLP1-RA benefit >5 mmol/mol" = "dodgerblue2")
) +
scale_colour_manual(
name = paste0("HbA1c benefit (mmol/mol) [n=", format(nrow(group.full.cohort),big.mark=",",scientific=FALSE),"]"),
labels = c(paste0("SGLT2i > 5 [n=", format(group.full.cohort %>% filter(intervals == levels(group.full.cohort$intervals)[1]) %>% nrow(),big.mark=",",scientific=FALSE), "]"),
paste0("SGLT2i 3 - 5 [n=", format(group.full.cohort %>% filter(intervals == levels(group.full.cohort$intervals)[2]) %>% nrow(),big.mark=",",scientific=FALSE), "]"),
paste0("SGLT2i 0 - 3 [n=", format(group.full.cohort %>% filter(intervals == levels(group.full.cohort$intervals)[3]) %>% nrow(),big.mark=",",scientific=FALSE), "]"),
paste0("GLP1-RA > 5 [n=", format(group.full.cohort %>% filter(intervals == levels(group.full.cohort$intervals)[4]) %>% nrow(),big.mark=",",scientific=FALSE), "]"),
paste0("GLP1-RA 3 - 5 [n=", format(group.full.cohort %>% filter(intervals == levels(group.full.cohort$intervals)[5]) %>% nrow(),big.mark=",",scientific=FALSE), "]"),
paste0("GLP1-RA 0 - 3 [n=", format(group.full.cohort %>% filter(intervals == levels(group.full.cohort$intervals)[6]) %>% nrow(),big.mark=",",scientific=FALSE), "]")),
breaks = c(levels(group.full.cohort$intervals)[1], levels(group.full.cohort$intervals)[2], levels(group.full.cohort$intervals)[3], levels(group.full.cohort$intervals)[6], levels(group.full.cohort$intervals)[5], levels(group.full.cohort$intervals)[4]),
values = c("SGLT2i benefit >5 mmol/mol" = "#f1a340",
"SGLT2i benefit 3-5 mmol/mol" = "#f1a340",
"SGLT2i benefit 0-3 mmol/mol" = "#f1a340",
"GLP1-RA benefit 0-3 mmol/mol" = "dodgerblue2",
"GLP1-RA benefit 3-5 mmol/mol" = "dodgerblue2",
"GLP1-RA benefit >5 mmol/mol" = "dodgerblue2")
) +
guides(
fill = guide_legend(title.position="top", title.hjust = 0.5, override.aes = list(alpha = c(1, 0.6, 0.2, 1, 0.6, 0.2)), shape = c(15,15,15,15,15,15), ncol = 2, nrow = 3),
colour = guide_legend(title.position="top", title.hjust = 0.5, override.aes = list(alpha = c(1, 0.6, 0.2, 1, 0.6, 0.2)), shape = c(15,15,15,15,15,15), ncol = 2, nrow = 3)
)
plot_preegfr_strata <- group.full.cohort %>%
select(intervals, preegfr) %>%
drop_na() %>%
ggplot(aes(x = intervals, y = preegfr)) +
geom_point(aes(fill = intervals, colour = intervals), alpha = 0, shape = 15, size = 5) +
geom_boxplot(aes(fill = intervals), alpha = c(1, 0.6, 0.2, 0.2, 0.6, 1), show.legend = F) +
ggtitle("eGFR") +
ylab(expression(paste("eGFR (mL/min/1.3", m^{2}, ")"))) +
scale_y_continuous(breaks = c(30, 60, 90, 120, 150)) +
theme_bw() +
annotate("point", x = 1, y = 9, shape = 15, colour = "#f1a340", size = 5, alpha = 1) +
annotate("point", x = 2, y = 9, shape = 15, colour = "#f1a340", size = 5, alpha = 0.6) +
annotate("point", x = 3, y = 9, shape = 15, colour = "#f1a340", size = 5, alpha = 0.2) +
annotate("point", x = 4, y = 9, shape = 15, colour = "dodgerblue2", size = 5, alpha = 0.2) +
annotate("point", x = 5, y = 9, shape = 15, colour = "dodgerblue2", size = 5, alpha = 0.6) +
annotate("point", x = 6, y = 9, shape = 15, colour = "dodgerblue2", size = 5, alpha = 1) +
coord_cartesian(ylim = c(20, 160), clip = "off") +
theme(legend.position = "bottom",
axis.text.y = element_text(size = 13),
axis.text.x = element_blank(),
axis.title.y = element_text(size = 13),
legend.text = element_text(size= 13 ),
legend.title = element_text(size = 13),
axis.title.x = element_text(vjust = -5, colour = "white"),
strip.background = element_rect(fill = "white"),
plot.title = element_text(hjust = 0.5)) +
scale_fill_manual(
name = paste0("HbA1c benefit (mmol/mol) [n=", format(nrow(group.full.cohort),big.mark=",",scientific=FALSE),"]"),
labels = c(paste0("SGLT2i > 5 [n=", format(group.full.cohort %>% filter(intervals == levels(group.full.cohort$intervals)[1]) %>% nrow(),big.mark=",",scientific=FALSE), "]"),
paste0("SGLT2i 3 - 5 [n=", format(group.full.cohort %>% filter(intervals == levels(group.full.cohort$intervals)[2]) %>% nrow(),big.mark=",",scientific=FALSE), "]"),
paste0("SGLT2i 0 - 3 [n=", format(group.full.cohort %>% filter(intervals == levels(group.full.cohort$intervals)[3]) %>% nrow(),big.mark=",",scientific=FALSE), "]"),
paste0("GLP1-RA > 5 [n=", format(group.full.cohort %>% filter(intervals == levels(group.full.cohort$intervals)[4]) %>% nrow(),big.mark=",",scientific=FALSE), "]"),
paste0("GLP1-RA 3 - 5 [n=", format(group.full.cohort %>% filter(intervals == levels(group.full.cohort$intervals)[5]) %>% nrow(),big.mark=",",scientific=FALSE), "]"),
paste0("GLP1-RA 0 - 3 [n=", format(group.full.cohort %>% filter(intervals == levels(group.full.cohort$intervals)[6]) %>% nrow(),big.mark=",",scientific=FALSE), "]")),
breaks = c(levels(group.full.cohort$intervals)[1], levels(group.full.cohort$intervals)[2], levels(group.full.cohort$intervals)[3], levels(group.full.cohort$intervals)[6], levels(group.full.cohort$intervals)[5], levels(group.full.cohort$intervals)[4]),
values = c("SGLT2i benefit >5 mmol/mol" = "#f1a340",
"SGLT2i benefit 3-5 mmol/mol" = "#f1a340",
"SGLT2i benefit 0-3 mmol/mol" = "#f1a340",
"GLP1-RA benefit 0-3 mmol/mol" = "dodgerblue2",
"GLP1-RA benefit 3-5 mmol/mol" = "dodgerblue2",
"GLP1-RA benefit >5 mmol/mol" = "dodgerblue2")
) +
scale_colour_manual(
name = paste0("HbA1c benefit (mmol/mol) [n=", format(nrow(group.full.cohort),big.mark=",",scientific=FALSE),"]"),
labels = c(paste0("SGLT2i > 5 [n=", format(group.full.cohort %>% filter(intervals == levels(group.full.cohort$intervals)[1]) %>% nrow(),big.mark=",",scientific=FALSE), "]"),
paste0("SGLT2i 3 - 5 [n=", format(group.full.cohort %>% filter(intervals == levels(group.full.cohort$intervals)[2]) %>% nrow(),big.mark=",",scientific=FALSE), "]"),
paste0("SGLT2i 0 - 3 [n=", format(group.full.cohort %>% filter(intervals == levels(group.full.cohort$intervals)[3]) %>% nrow(),big.mark=",",scientific=FALSE), "]"),
paste0("GLP1-RA > 5 [n=", format(group.full.cohort %>% filter(intervals == levels(group.full.cohort$intervals)[4]) %>% nrow(),big.mark=",",scientific=FALSE), "]"),
paste0("GLP1-RA 3 - 5 [n=", format(group.full.cohort %>% filter(intervals == levels(group.full.cohort$intervals)[5]) %>% nrow(),big.mark=",",scientific=FALSE), "]"),
paste0("GLP1-RA 0 - 3 [n=", format(group.full.cohort %>% filter(intervals == levels(group.full.cohort$intervals)[6]) %>% nrow(),big.mark=",",scientific=FALSE), "]")),
breaks = c(levels(group.full.cohort$intervals)[1], levels(group.full.cohort$intervals)[2], levels(group.full.cohort$intervals)[3], levels(group.full.cohort$intervals)[6], levels(group.full.cohort$intervals)[5], levels(group.full.cohort$intervals)[4]),
values = c("SGLT2i benefit >5 mmol/mol" = "#f1a340",
"SGLT2i benefit 3-5 mmol/mol" = "#f1a340",
"SGLT2i benefit 0-3 mmol/mol" = "#f1a340",
"GLP1-RA benefit 0-3 mmol/mol" = "dodgerblue2",
"GLP1-RA benefit 3-5 mmol/mol" = "dodgerblue2",
"GLP1-RA benefit >5 mmol/mol" = "dodgerblue2")
) +
guides(
fill = guide_legend(title.position="top", title.hjust = 0.5, override.aes = list(alpha = c(1, 0.6, 0.2, 1, 0.6, 0.2)), shape = c(15,15,15,15,15,15), ncol = 2, nrow = 3),
colour = guide_legend(title.position="top", title.hjust = 0.5, override.aes = list(alpha = c(1, 0.6, 0.2, 1, 0.6, 0.2)), shape = c(15,15,15,15,15,15), ncol = 2, nrow = 3)
)
plot_agetx_strata <- group.full.cohort %>%
select(intervals, agetx) %>%
drop_na() %>%
ggplot(aes(x = intervals, y = agetx)) +
geom_point(aes(fill = intervals, colour = intervals), alpha = 0, shape = 15, size = 5) +
geom_boxplot(aes(fill = intervals), alpha = c(1, 0.6, 0.2, 0.2, 0.6, 1), show.legend = F) +
ggtitle("Current age") +
ylab("Current age (years)") +
theme_bw() +
annotate("point", x = 1, y = 5, shape = 15, colour = "#f1a340", size = 5, alpha = 1) +
annotate("point", x = 2, y = 5, shape = 15, colour = "#f1a340", size = 5, alpha = 0.6) +
annotate("point", x = 3, y = 5, shape = 15, colour = "#f1a340", size = 5, alpha = 0.2) +
annotate("point", x = 4, y = 5, shape = 15, colour = "dodgerblue2", size = 5, alpha = 0.2) +
annotate("point", x = 5, y = 5, shape = 15, colour = "dodgerblue2", size = 5, alpha = 0.6) +
annotate("point", x = 6, y = 5, shape = 15, colour = "dodgerblue2", size = 5, alpha = 1) +
coord_cartesian(ylim = c(12, 100), clip = "off") +
theme(legend.position = "bottom",
axis.text.y = element_text(size = 13),
axis.text.x = element_blank(),
axis.title.y = element_text(size = 13),
legend.text = element_text(size= 13 ),
legend.title = element_text(size = 13),
axis.title.x = element_text(vjust = -5, colour = "white"),
strip.background = element_rect(fill = "white"),
plot.title = element_text(hjust = 0.5)) +
scale_fill_manual(
name = paste0("HbA1c benefit (mmol/mol) [n=", format(nrow(group.full.cohort),big.mark=",",scientific=FALSE),"]"),
labels = c(paste0("SGLT2i > 5 [n=", format(group.full.cohort %>% filter(intervals == levels(group.full.cohort$intervals)[1]) %>% nrow(),big.mark=",",scientific=FALSE), "]"),
paste0("SGLT2i 3 - 5 [n=", format(group.full.cohort %>% filter(intervals == levels(group.full.cohort$intervals)[2]) %>% nrow(),big.mark=",",scientific=FALSE), "]"),
paste0("SGLT2i 0 - 3 [n=", format(group.full.cohort %>% filter(intervals == levels(group.full.cohort$intervals)[3]) %>% nrow(),big.mark=",",scientific=FALSE), "]"),
paste0("GLP1-RA > 5 [n=", format(group.full.cohort %>% filter(intervals == levels(group.full.cohort$intervals)[4]) %>% nrow(),big.mark=",",scientific=FALSE), "]"),
paste0("GLP1-RA 3 - 5 [n=", format(group.full.cohort %>% filter(intervals == levels(group.full.cohort$intervals)[5]) %>% nrow(),big.mark=",",scientific=FALSE), "]"),
paste0("GLP1-RA 0 - 3 [n=", format(group.full.cohort %>% filter(intervals == levels(group.full.cohort$intervals)[6]) %>% nrow(),big.mark=",",scientific=FALSE), "]")),
breaks = c(levels(group.full.cohort$intervals)[1], levels(group.full.cohort$intervals)[2], levels(group.full.cohort$intervals)[3], levels(group.full.cohort$intervals)[6], levels(group.full.cohort$intervals)[5], levels(group.full.cohort$intervals)[4]),
values = c("SGLT2i benefit >5 mmol/mol" = "#f1a340",
"SGLT2i benefit 3-5 mmol/mol" = "#f1a340",
"SGLT2i benefit 0-3 mmol/mol" = "#f1a340",
"GLP1-RA benefit 0-3 mmol/mol" = "dodgerblue2",
"GLP1-RA benefit 3-5 mmol/mol" = "dodgerblue2",
"GLP1-RA benefit >5 mmol/mol" = "dodgerblue2")
) +
scale_colour_manual(
name = paste0("HbA1c benefit (mmol/mol) [n=", format(nrow(group.full.cohort),big.mark=",",scientific=FALSE),"]"),
labels = c(paste0("SGLT2i > 5 [n=", format(group.full.cohort %>% filter(intervals == levels(group.full.cohort$intervals)[1]) %>% nrow(),big.mark=",",scientific=FALSE), "]"),
paste0("SGLT2i 3 - 5 [n=", format(group.full.cohort %>% filter(intervals == levels(group.full.cohort$intervals)[2]) %>% nrow(),big.mark=",",scientific=FALSE), "]"),
paste0("SGLT2i 0 - 3 [n=", format(group.full.cohort %>% filter(intervals == levels(group.full.cohort$intervals)[3]) %>% nrow(),big.mark=",",scientific=FALSE), "]"),
paste0("GLP1-RA > 5 [n=", format(group.full.cohort %>% filter(intervals == levels(group.full.cohort$intervals)[4]) %>% nrow(),big.mark=",",scientific=FALSE), "]"),
paste0("GLP1-RA 3 - 5 [n=", format(group.full.cohort %>% filter(intervals == levels(group.full.cohort$intervals)[5]) %>% nrow(),big.mark=",",scientific=FALSE), "]"),
paste0("GLP1-RA 0 - 3 [n=", format(group.full.cohort %>% filter(intervals == levels(group.full.cohort$intervals)[6]) %>% nrow(),big.mark=",",scientific=FALSE), "]")),
breaks = c(levels(group.full.cohort$intervals)[1], levels(group.full.cohort$intervals)[2], levels(group.full.cohort$intervals)[3], levels(group.full.cohort$intervals)[6], levels(group.full.cohort$intervals)[5], levels(group.full.cohort$intervals)[4]),
values = c("SGLT2i benefit >5 mmol/mol" = "#f1a340",
"SGLT2i benefit 3-5 mmol/mol" = "#f1a340",
"SGLT2i benefit 0-3 mmol/mol" = "#f1a340",
"GLP1-RA benefit 0-3 mmol/mol" = "dodgerblue2",
"GLP1-RA benefit 3-5 mmol/mol" = "dodgerblue2",
"GLP1-RA benefit >5 mmol/mol" = "dodgerblue2")
) +
guides(
fill = guide_legend(title.position="top", title.hjust = 0.5, override.aes = list(alpha = c(1, 0.6, 0.2, 1, 0.6, 0.2)), shape = c(15,15,15,15,15,15), ncol = 2, nrow = 3),
colour = guide_legend(title.position="top", title.hjust = 0.5, override.aes = list(alpha = c(1, 0.6, 0.2, 1, 0.6, 0.2)), shape = c(15,15,15,15,15,15), ncol = 2, nrow = 3)
)
plot_prebmi_strata <- group.full.cohort %>%
select(intervals, prebmi) %>%
drop_na() %>%
ggplot(aes(x = intervals, y = prebmi)) +
geom_point(aes(fill = intervals, colour = intervals), alpha = 0, shape = 15, size = 5) +
geom_boxplot(aes(fill = intervals), alpha = c(1, 0.6, 0.2, 0.2, 0.6, 1), show.legend = F) +
ggtitle("BMI") +
ylab(expression(paste("BMI (kg/", m^{2}, ")"))) +
theme_bw() +
annotate("point", x = 1, y = 8, shape = 15, colour = "#f1a340", size = 5, alpha = 1) +
annotate("point", x = 2, y = 8, shape = 15, colour = "#f1a340", size = 5, alpha = 0.6) +
annotate("point", x = 3, y = 8, shape = 15, colour = "#f1a340", size = 5, alpha = 0.2) +
annotate("point", x = 4, y = 8, shape = 15, colour = "dodgerblue2", size = 5, alpha = 0.2) +
annotate("point", x = 5, y = 8, shape = 15, colour = "dodgerblue2", size = 5, alpha = 0.6) +
annotate("point", x = 6, y = 8, shape = 15, colour = "dodgerblue2", size = 5, alpha = 1) +
coord_cartesian(ylim = c(15, 100), clip = "off") +
theme(legend.position = "bottom",
axis.text.y = element_text(size = 13),
axis.text.x = element_blank(),
axis.title.y = element_text(size = 13),
legend.text = element_text(size= 13 ),
legend.title = element_text(size = 13),
axis.title.x = element_text(vjust = -5, colour = "white"),
strip.background = element_rect(fill = "white"),
plot.title = element_text(hjust = 0.5)) +
scale_fill_manual(
name = paste0("HbA1c benefit (mmol/mol) [n=", format(nrow(group.full.cohort),big.mark=",",scientific=FALSE),"]"),
labels = c(paste0("SGLT2i > 5 [n=", format(group.full.cohort %>% filter(intervals == levels(group.full.cohort$intervals)[1]) %>% nrow(),big.mark=",",scientific=FALSE), "]"),
paste0("SGLT2i 3 - 5 [n=", format(group.full.cohort %>% filter(intervals == levels(group.full.cohort$intervals)[2]) %>% nrow(),big.mark=",",scientific=FALSE), "]"),
paste0("SGLT2i 0 - 3 [n=", format(group.full.cohort %>% filter(intervals == levels(group.full.cohort$intervals)[3]) %>% nrow(),big.mark=",",scientific=FALSE), "]"),
paste0("GLP1-RA > 5 [n=", format(group.full.cohort %>% filter(intervals == levels(group.full.cohort$intervals)[4]) %>% nrow(),big.mark=",",scientific=FALSE), "]"),
paste0("GLP1-RA 3 - 5 [n=", format(group.full.cohort %>% filter(intervals == levels(group.full.cohort$intervals)[5]) %>% nrow(),big.mark=",",scientific=FALSE), "]"),
paste0("GLP1-RA 0 - 3 [n=", format(group.full.cohort %>% filter(intervals == levels(group.full.cohort$intervals)[6]) %>% nrow(),big.mark=",",scientific=FALSE), "]")),
breaks = c(levels(group.full.cohort$intervals)[1], levels(group.full.cohort$intervals)[2], levels(group.full.cohort$intervals)[3], levels(group.full.cohort$intervals)[6], levels(group.full.cohort$intervals)[5], levels(group.full.cohort$intervals)[4]),
values = c("SGLT2i benefit >5 mmol/mol" = "#f1a340",
"SGLT2i benefit 3-5 mmol/mol" = "#f1a340",
"SGLT2i benefit 0-3 mmol/mol" = "#f1a340",
"GLP1-RA benefit 0-3 mmol/mol" = "dodgerblue2",
"GLP1-RA benefit 3-5 mmol/mol" = "dodgerblue2",
"GLP1-RA benefit >5 mmol/mol" = "dodgerblue2")
) +
scale_colour_manual(
name = paste0("HbA1c benefit (mmol/mol) [n=", format(nrow(group.full.cohort),big.mark=",",scientific=FALSE),"]"),
labels = c(paste0("SGLT2i > 5 [n=", format(group.full.cohort %>% filter(intervals == levels(group.full.cohort$intervals)[1]) %>% nrow(),big.mark=",",scientific=FALSE), "]"),
paste0("SGLT2i 3 - 5 [n=", format(group.full.cohort %>% filter(intervals == levels(group.full.cohort$intervals)[2]) %>% nrow(),big.mark=",",scientific=FALSE), "]"),
paste0("SGLT2i 0 - 3 [n=", format(group.full.cohort %>% filter(intervals == levels(group.full.cohort$intervals)[3]) %>% nrow(),big.mark=",",scientific=FALSE), "]"),
paste0("GLP1-RA > 5 [n=", format(group.full.cohort %>% filter(intervals == levels(group.full.cohort$intervals)[4]) %>% nrow(),big.mark=",",scientific=FALSE), "]"),
paste0("GLP1-RA 3 - 5 [n=", format(group.full.cohort %>% filter(intervals == levels(group.full.cohort$intervals)[5]) %>% nrow(),big.mark=",",scientific=FALSE), "]"),
paste0("GLP1-RA 0 - 3 [n=", format(group.full.cohort %>% filter(intervals == levels(group.full.cohort$intervals)[6]) %>% nrow(),big.mark=",",scientific=FALSE), "]")),
breaks = c(levels(group.full.cohort$intervals)[1], levels(group.full.cohort$intervals)[2], levels(group.full.cohort$intervals)[3], levels(group.full.cohort$intervals)[6], levels(group.full.cohort$intervals)[5], levels(group.full.cohort$intervals)[4]),
values = c("SGLT2i benefit >5 mmol/mol" = "#f1a340",
"SGLT2i benefit 3-5 mmol/mol" = "#f1a340",
"SGLT2i benefit 0-3 mmol/mol" = "#f1a340",
"GLP1-RA benefit 0-3 mmol/mol" = "dodgerblue2",
"GLP1-RA benefit 3-5 mmol/mol" = "dodgerblue2",
"GLP1-RA benefit >5 mmol/mol" = "dodgerblue2")
) +
guides(
fill = guide_legend(title.position="top", title.hjust = 0.5, override.aes = list(alpha = c(1, 0.6, 0.2, 1, 0.6, 0.2)), shape = c(15,15,15,15,15,15), ncol = 2, nrow = 3),
colour = guide_legend(title.position="top", title.hjust = 0.5, override.aes = list(alpha = c(1, 0.6, 0.2, 1, 0.6, 0.2)), shape = c(15,15,15,15,15,15), ncol = 2, nrow = 3)
)
plot_main_2.1 <- patchwork::wrap_plots(list(
plot_sex_strata,
plot_prehba1c_strata,
plot_preegfr_strata,
plot_agetx_strata,
plot_prebmi_strata
), nrow = 1) +
plot_layout(guides = 'collect') & theme(legend.position = "bottom")
plot_main_2.1 <- patchwork::wrap_plots(list(
plot_sex_strata +
theme(
legend.position = "bottom"
),
patchwork::wrap_plots(list(
plot_prehba1c_strata,
plot_preegfr_strata,
plot_agetx_strata,
plot_prebmi_strata
), nrow = 1) +
plot_layout(guides = "collect") &
theme(
legend.position = "bottom"
)
), nrow = 1) +
plot_layout(
widths = c(1, 5)
)
pdf(width = 17, height = 8, "Plots/Paper/Manuscript/11.08.plot_main_2.1.pdf")
plot_main_2.1
dev.off()
#:------------------------------------------------------------------------------
# Figure 3: 6 panel plot:
# -A. Predicted HbA1c change for each clinical subgroup
# -B. Predicted weight change for each clinical subgroup
# -C. Discontinuation levels for each clinical subgroup
# -D. Risk of microvascular complications
# -E. Risk of CVD/MACE
# -F. Risk of heart failure
require(forestplot)
require(grid)
### A - HbA1c
# levels needed
interval_breaks <- c(-5, -3, 0, 3, 5)
## Read in propensity scores
patient_prop_scores <- readRDS("Samples/SGLT2-GLP1/Aurum/ps_model/patient_prop_scores.rds")
## Read in treatment effects
treatment_effects <- readRDS("Samples/SGLT2-GLP1/Aurum/response_model_bcf/patient_effects.rds")
# Overall population
hba1c <- set_up_data_sglt2_glp1(dataset.type = "full.cohort") %>%
left_join(patient_prop_scores, by = c("patid", "pated")) %>%
left_join(treatment_effects, by = c("patid", "pated"))
# split population into groups
group.hba1c.dataset <- group_values(data = hba1c,
variable = "effects",
breaks = interval_breaks) %>%
drop_na(intervals) %>%
rename("hba1c_diff" = "effects")
# predictions for the hba1c adjusted model
predictions_hba1c_stan_adjusted_overall <- readRDS("Samples/SGLT2-GLP1/Aurum/additional_outcomes/predictions_hba1c_stan_adjusted_overall.rds") %>%
mutate(mean = as.numeric(mean),
lci = as.numeric(lci),
uci = as.numeric(uci))
# predictions for the hba1c adjusted model full
predictions_hba1c_stan_adjusted_full <- readRDS("Samples/SGLT2-GLP1/Aurum/additional_outcomes/predictions_hba1c_stan_adjusted_full.rds") %>%
mutate(mean = as.numeric(mean),
lci = as.numeric(lci),
uci = as.numeric(uci))
# calculate axis limits for the plots
hba1c_strata_axis_min <- plyr::round_any(floor(min(c(predictions_hba1c_stan_adjusted_overall %>% select(c("mean","lci","uci")) %>% min(),
predictions_hba1c_stan_adjusted_full %>% select(c("mean","lci","uci")) %>% min()))), 5, f = floor)
hba1c_strata_axis_max <- plyr::round_any(floor(max(c(predictions_hba1c_stan_adjusted_overall %>% select(c("mean","lci","uci")) %>% max(),
predictions_hba1c_stan_adjusted_full %>% select(c("mean","lci","uci")) %>% max()))), 5, f = ceiling)
# plot predicted hba1c change
plot_a <- rbind(
cbind(intervals = "Predicted HbA1c benefit on SGLT2i", mean = 50, lci = 50, uci = 50, drugclass = "SGLT2"),
cbind(intervals = "Predicted HbA1c benefit on SGLT2i", mean = 50, lci = 50, uci = 50, drugclass = "GLP1"),
predictions_hba1c_stan_adjusted_overall %>% select(intervals, drugclass, mean, lci, uci) %>% slice(1:6),
cbind(intervals = "Predicted HbA1c benefit on GLP1-RA", mean = 50, lci = 50, uci = 50, drugclass = "SGLT2"),
cbind(intervals = "Predicted HbA1c benefit on GLP1-RA", mean = 50, lci = 50, uci = 50, drugclass = "GLP1"),
predictions_hba1c_stan_adjusted_overall %>% select(intervals, drugclass, mean, lci, uci) %>% slice(7:12),
predictions_hba1c_stan_adjusted_full %>% select(drugclass, mean, lci, uci) %>% mutate(intervals = "Average treatment effect")
) %>%
as.data.frame() %>%
mutate(mean = as.numeric(mean),
lci = as.numeric(lci),
uci = as.numeric(uci),
intervals = ifelse(intervals == levels(group.hba1c.dataset$intervals)[1], paste0(">5 mmol/mol (n=", format(group.hba1c.dataset%>%filter(intervals == levels(group.hba1c.dataset$intervals)[1])%>%nrow(),big.mark=",",scientific=FALSE), ")"),
ifelse(intervals == levels(group.hba1c.dataset$intervals)[2], paste0("3-5 mmol/mol (n=", format(group.hba1c.dataset%>%filter(intervals == levels(group.hba1c.dataset$intervals)[2])%>%nrow(),big.mark=",",scientific=FALSE), ")"),
ifelse(intervals == levels(group.hba1c.dataset$intervals)[3], paste0("0-3 mmol/mol (n=", format(group.hba1c.dataset%>%filter(intervals == levels(group.hba1c.dataset$intervals)[3])%>%nrow(),big.mark=",",scientific=FALSE), ")"),
ifelse(intervals == levels(group.hba1c.dataset$intervals)[4], paste0("0-3 mmol/mol (n=", format(group.hba1c.dataset%>%filter(intervals == levels(group.hba1c.dataset$intervals)[4])%>%nrow(),big.mark=",",scientific=FALSE), ")"),
ifelse(intervals == levels(group.hba1c.dataset$intervals)[5], paste0("3-5 mmol/mol (n=", format(group.hba1c.dataset%>%filter(intervals == levels(group.hba1c.dataset$intervals)[5])%>%nrow(),big.mark=",",scientific=FALSE), ")"),
ifelse(intervals == levels(group.hba1c.dataset$intervals)[6], paste0(">5 mmol/mol (n=", format(group.hba1c.dataset%>%filter(intervals == levels(group.hba1c.dataset$intervals)[6])%>%nrow(),big.mark=",",scientific=FALSE), ")"), intervals))))))) %>%
rename("lower" = "lci", "upper" = "uci", "group" = "drugclass", "labeltext" = "intervals") %>%
group_by(group) %>%
mutate(group = ifelse(group == "SGLT2", "SGLT2i", "GLP1-RA")) %>%
forestplot(ci.vertices = TRUE,
fn.ci_norm = c(fpDrawNormalCI, fpDrawNormalCI, fpDrawNormalCI, fpDrawNormalCI, fpDrawNormalCI, fpDrawNormalCI, fpDrawNormalCI, fpDrawNormalCI, fpDrawNormalCI, fpDrawDiamondCI),
ci.vertices.height = 0.1,
title = "Average HbA1c change",
clip = c(hba1c_strata_axis_min, hba1c_strata_axis_max),
xticks = seq(hba1c_strata_axis_min, hba1c_strata_axis_max, 5),
boxsize = .2,
txt_gp = fpTxtGp(ticks=gpar(cex=0.8), xlab=gpar(cex=1)),
xlab = "Average HbA1c change (mmol/mol)") %>%
fp_add_header(paste0("Overall population (n=", format(group.hba1c.dataset%>%nrow(),big.mark=",",scientific=FALSE), ")")) %>%
fp_set_style(box = c("#f1a340", "dodgerblue2") |> lapply(function(x) gpar(fill = x, col = "#555555")),
default = gpar(vertices = TRUE)) %>%
fp_add_lines(h_2 = "black",
h_6 = gpar(col = "black", lty = 2),
h_10 = "black")
### B - Weight
weight.dataset <- set_up_data_sglt2_glp1(dataset.type = "weight.dataset") %>%
left_join(patient_prop_scores, by = c("patid", "pated")) %>%
left_join(treatment_effects, by = c("patid", "pated")) %>%
mutate(w.change = postweight - preweight)
group.weight.dataset <- group_values(data = weight.dataset,
variable = "effects",
breaks = interval_breaks) %>%
drop_na(intervals)
# predictions for the weight adjusted model
predictions_weight_stan_adjusted_overall <- readRDS("Samples/SGLT2-GLP1/Aurum/additional_outcomes/predictions_weight_stan_adjusted_overall.rds")
# predictions for the weight adjusted model full
predictions_weight_stan_adjusted_full <- readRDS("Samples/SGLT2-GLP1/Aurum/additional_outcomes/predictions_weight_stan_adjusted_full.rds")
weight_strata_axis_min <- plyr::round_any(floor(min(c(predictions_weight_stan_adjusted_overall %>% select(c("mean","lci","uci")) %>% as.data.frame() %>% gather() %>% select(value) %>% unlist() %>% as.numeric() %>% min(),
predictions_weight_stan_adjusted_full %>% select(c("mean","lci","uci")) %>% as.data.frame() %>% gather() %>% select(value) %>% unlist() %>% as.numeric() %>% min()))), 1, f = floor)
weight_strata_axis_max <- plyr::round_any(ceiling(max(c(predictions_weight_stan_adjusted_overall %>% select(c("mean","lci","uci")) %>% as.data.frame() %>% gather() %>% select(value) %>% unlist() %>% as.numeric() %>% max(),
predictions_weight_stan_adjusted_full %>% select(c("mean","lci","uci")) %>% as.data.frame() %>% gather() %>% select(value) %>% unlist() %>% as.numeric() %>% max()))), 2, f = ceiling)
plot_b <- rbind(
cbind(mean = 50, lci = 50, uci = 50, drugclass = "SGLT2", intervals = "Predicted HbA1c benefit on SGLT2i"),
cbind(mean = 50, lci = 50, uci = 50, drugclass = "GLP1", intervals = "Predicted HbA1c benefit on SGLT2i"),
predictions_weight_stan_adjusted_overall %>%
slice(c(1:6)),
cbind(mean = 50, lci = 50, uci = 50, drugclass = "SGLT2", intervals = "Predicted HbA1c benefit on GLP1-RA"),
cbind(mean = 50, lci = 50, uci = 50, drugclass = "GLP1", intervals = "Predicted HbA1c benefit on GLP1-RA"),
predictions_weight_stan_adjusted_overall %>%
slice(-c(1:6)),
predictions_weight_stan_adjusted_full %>% cbind(intervals = "Average treatment effect")
) %>%
as.data.frame() %>%
mutate(mean = as.numeric(mean),
lci = as.numeric(lci),
intervals = ifelse(intervals == levels(group.weight.dataset$intervals)[1], paste0(">5 mmol/mol (n=", format(group.weight.dataset%>%filter(intervals==levels(group.weight.dataset$intervals)[1])%>%nrow(),big.mark=",",scientific=FALSE),")"),
ifelse(intervals == levels(group.weight.dataset$intervals)[2], paste0("3-5 mmol/mol (n=", format(group.weight.dataset%>%filter(intervals==levels(group.weight.dataset$intervals)[2])%>%nrow(),big.mark=",",scientific=FALSE), ")"),
ifelse(intervals == levels(group.weight.dataset$intervals)[3], paste0("0-3 mmol/mol (n=", format(group.weight.dataset%>%filter(intervals==levels(group.weight.dataset$intervals)[3])%>%nrow(),big.mark=",",scientific=FALSE),")"),
ifelse(intervals == levels(group.weight.dataset$intervals)[4], paste0("0-3 mmol/mol (n=", format(group.weight.dataset%>%filter(intervals==levels(group.weight.dataset$intervals)[4])%>%nrow(),big.mark=",",scientific=FALSE),")"),
ifelse(intervals == levels(group.weight.dataset$intervals)[5], paste0("3-5 mmol/mol (n=", format(group.weight.dataset%>%filter(intervals==levels(group.weight.dataset$intervals)[5])%>%nrow(),big.mark=",",scientific=FALSE),")"),
ifelse(intervals == levels(group.weight.dataset$intervals)[6], paste0(">5 mmol/mol (n=", format(group.weight.dataset%>%filter(intervals==levels(group.weight.dataset$intervals)[6])%>%nrow(),big.mark=",",scientific=FALSE),")"), intervals)))))),
uci = as.numeric(uci)) %>%
rename("lower" = "lci", "upper" = "uci", "group" = "drugclass", "labeltext" = "intervals") %>%
group_by(group) %>%
mutate(group = ifelse(group == "SGLT2", "SGLT2i", "GLP1-RA")) %>%
forestplot(ci.vertices = TRUE,
fn.ci_norm = c(fpDrawNormalCI, fpDrawNormalCI, fpDrawNormalCI, fpDrawNormalCI, fpDrawNormalCI, fpDrawNormalCI, fpDrawNormalCI, fpDrawNormalCI, fpDrawNormalCI, fpDrawDiamondCI),
ci.vertices.height = 0.1,
title = "Average weight change",
clip = c(weight_strata_axis_min, weight_strata_axis_max),
xticks = seq(weight_strata_axis_min, weight_strata_axis_max, 1),
boxsize = .2,
txt_gp = fpTxtGp(ticks=gpar(cex=0.8), xlab=gpar(cex=1)),
xlab = "Average weight change (kg)") %>%
fp_add_header(paste0("Overall population (n=", format(group.weight.dataset%>%nrow(),big.mark=",",scientific=FALSE), ")")) %>%
fp_set_style(box = c("#f1a340", "dodgerblue2") |> lapply(function(x) gpar(fill = x, col = "#555555")),
default = gpar(vertices = TRUE)) %>%
fp_add_lines(h_2 = "black",
h_6 = gpar(col = "black", lty = 2),
h_10 = "black")
### C - Discontinuation
discontinuation.dataset <- set_up_data_sglt2_glp1(dataset.type = "discontinuation.dataset") %>%
left_join(patient_prop_scores, by = c("patid", "pated")) %>%
left_join(treatment_effects, by = c("patid", "pated")) %>%
mutate(stopdrug_6m_3mFU = factor(stopdrug_6m_3mFU))
group.discontinuation.dataset <- group_values(data = discontinuation.dataset,
variable = "effects",
breaks = interval_breaks) %>%
drop_na(intervals)
# predictions for the discontinuation adjusted model
predictions_discontinuation_stan_adjusted_overall <- readRDS("Samples/SGLT2-GLP1/Aurum/additional_outcomes/predictions_discontinuation_stan_adjusted_overall.rds")
# predictions for the discontinuation model sex strata
predictions_discontinuation_stan_adjusted_full <- readRDS("Samples/SGLT2-GLP1/Aurum/additional_outcomes/predictions_discontinuation_stan_adjusted_full.rds")
discontinuation_overall_axis_max <- plyr::round_any(ceiling(max(c(predictions_discontinuation_stan_adjusted_overall %>% select(c("mean","lci","uci")) %>% as.data.frame() %>% gather() %>% select(value) %>% unlist() %>% as.numeric() %>% max() * 100,
predictions_discontinuation_stan_adjusted_full %>% select(c("mean","lci","uci")) %>% as.data.frame() %>% gather() %>% select(value) %>% unlist() %>% as.numeric() %>% max() * 100))), 5, f = ceiling)
discontinuation_strata_axis_max <- plyr::round_any(ceiling(max(c(predictions_discontinuation_stan_adjusted_overall %>% select(c("mean","lci","uci")) %>% as.data.frame() %>% gather() %>% select(value) %>% unlist() %>% as.numeric() %>% max() * 100,
predictions_discontinuation_stan_adjusted_full %>% select(c("mean","lci","uci")) %>% as.data.frame() %>% gather() %>% select(value) %>% unlist() %>% as.numeric() %>% max() * 100))), 5, f = ceiling)
plot_c <- rbind(
cbind(mean = 150, lci = 150, uci = 150, drugclass = "SGLT2", intervals = "Predicted HbA1c benefit on SGLT2i"),
cbind(mean = 150, lci = 150, uci = 150, drugclass = "GLP1", intervals = "Predicted HbA1c benefit on SGLT2i"),
predictions_discontinuation_stan_adjusted_overall %>%
slice(c(1:6)) %>%
mutate(mean = as.numeric(mean)*100,
lci = as.numeric(lci)*100,
uci = as.numeric(uci)*100),
cbind(mean = 150, lci = 150, uci = 150, drugclass = "SGLT2", intervals = "Predicted HbA1c benefit on GLP1-RA"),
cbind(mean = 150, lci = 150, uci = 150, drugclass = "GLP1", intervals = "Predicted HbA1c benefit on GLP1-RA"),
predictions_discontinuation_stan_adjusted_overall %>%
slice(-c(1:6)) %>%
mutate(mean = as.numeric(mean)*100,
lci = as.numeric(lci)*100,
uci = as.numeric(uci)*100),